Measures of Fit for Calibrated Models

I. Introduction Economists have long debated appropriate methods for assessing the empirical relevance of economic models. The standard econometric approach can be traced back to Haavelmo (1944), who argued that an economic model should be embedded within a complete probability model and analyzed using statistical methods designed for conducting inference about unknown probability distributions. In the modern literature, this approach is clearly exemplified in work such as that of L. Hansen and Sargent (1980) or McFadden (1981). How­ever, many economic models do not provide a realistic and complete probability structure for the variables under consideration. To analyze these models using standard econometric methods, they must first be augmented with additional random components. Inferences drawn from these expanded models are meaningful only to the extent that the additional random components do not mask or change the salient features of the original economic models.